Wednesday, August 28, 2013

Announcing CAFA 2: The Second Critical Assessment of Protein Function Annotations

Just received this from Iddo Friedberg:

Friends and Colleagues,

We are pleased to announce the Second Critical Assessment of protein
Function Annotation (CAFA) challenge. In CAFA 2, we would like to
evaluate the performance of protein function prediction tools/methods
(in old and new scenarios) and also expand the challenge to include
prediction of human phenotypes associated with genes and gene
products. As the last time, CAFA will be a part of the Automated
Function Prediction Special Interest Group (AFP-SIG) meeting that will
be held alongside the ISMB conference. AFP-SIG will be held as a
two-day meeting in July 2014 in Boston.

The targets and all information about the CAFA challenge are now
available at http://biofunctionprediction.org. The submission deadline
for predictions is January 15, 2014. The initial evaluation will be
done during the AFP-SIG meeting in Boston. Anyone in the world is
welcome to participate.

The mission of the Automated Function Prediction Special Interest
Group (AFP-SIG) is to bring together computational biologists who are
dealing with the important problem of gene and gene product function
prediction, to share ideas and create collaborations. We also aim to
facilitate interactions with experimental biologists and biocurators.
We hope that AFP-SIG serves an important role in stimulating research
in annotation of biological macromolecules, but also related fields.

About the CAFA experiment

The problem: There are far too many proteins for which the sequence is
known, but the function is not. The gap between what we know and what
we do not know is growing. A major challenge in the field of
bioinformatics is to predict the function of a protein from its
sequence (and all other data one can find). At the same time, how can
we judge how well these function prediction algorithms are performing
and whether we are making progress over time?

The solution: The Critical Assessment of protein Function Annotation
algorithms (CAFA) is an experiment designed to provide a large-scale
assessment of computational methods dedicated to predicting protein
function. We will evaluate methods in predicting the Gene Ontology
(GO) terms in the categories of Molecular Function, Biological
Process, and Cellular Component. In addition, predictors may use the
Human Phenotype Ontology (HPO) for the human dataset. A set of protein
sequences is provided by the organizers, and participants are expected
to submit their predictions by the submission deadline, January 15,
2014. The predictions will be evaluated during the Automated Function
Prediction (AFP) meeting, which has been approved as a Special
Interest Group (SIG) meeting, at the ISMB 2014 conference (Boston,
USA).

History: The first CAFA experiment was conducted in 2010-2011.
Twenty-three groups submitted fifty-four algorithms for assessment.
The results and most methods were published in Nature Methods and in a
special supplement in BMC Bioinformatics. CAFA 1 has brought together
a large group of computational predictors and, for the first time,
provided us with a clear picture of the state of this important field.
As with other critical assessment experiments, the aim of CAFA is
improve protein function prediction by continuously challenging groups
to develop more accurate methods.


How to participate in CAFA 2?
1. Download target proteins, available August 27, 2013
2. Submit predictions on or before January 15, 2014
3. Join us at the AFP-SIG, July 11-12, 2014 in Boston for the eighth
protein function prediction meeting, to hear the CAFA 2 results, to
present your work, and to learn about the latest research in
computational protein function prediction

More details at: http://biofunctionprediction.org

Confirmed keynote speakers:
Fiona Brinkman, Simon-Fraser University, Canada
Mark Gerstein, Yale University, USA

Looking forward to hearing from you!
The CAFA organizing Team: Predrag Radivojac, Michal Linial, Sean
Mooney and Iddo Friedberg

Contact: CAFA.2014@gmail.com

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